Polygalacturonases from various sources have been analyzed by ClustalW and T-COFFEE, for identification of conserved and functional motifs in them. All the 104 polygalacturonases analyzed by the above programs, revealed four highly conserved motifs, viz., NTD, G/QDD, G/SHG and RIK among them. Distance conservation between the motifs was also observed. Based on the available evidences from chemi...

UNLABELLED Many DNA functional motifs tend to accumulate or cluster at specific gene locations. These locations can be detected, in a group of gene sequences, as high frequency 'peaks' with respect to a reference position, such as the transcription start site (TSS). We have developed a web tool for the identification of regions containing significant motif peaks. We show, by using different yea...

The transcriptional network of Escherichia coli is currently the best-understood regulatory network of a single cell. Motivated by statistical evidence, suggesting a hierarchical modular architecture in this network, we identified eight modules with well-defined physiological functions. These modules were identified by a clustering approach, using the shortest path to trace regulatory relations...

Understanding the structural repertoire of RNA is crucial for RNA genomics research. Yet current methods for finding novel RNAs are limited to small or known RNA families. To expand known RNA structural motifs, we develop a two-dimensional graphical representation approach for describing and estimating the size of RNA's secondary structural repertoire, including naturally occurring and other po...

The study of disease often hinges on the biological function of proteins, but determining protein function is a difficult experimental process. To minimize duplicated effort, algorithms for function prediction seek characteristics indicative of possible protein function. One approach is to identify substructural matches of geometric and chemical similarity between motifs representing known acti...

The identification of sequence motifs is a fundamental method for suggesting good candidates for biologically functional regions such as promoters, splice sites, binding sites, etc. We investigate the following approach to identifying motifs: given a collection of orthologous sequences from multiple species related by a known phylogenetic tree, search for motifs that are well conserved (accordi...

Naturally occurring proteins in cellular networks often share peptide motifs. These motifs have been known to play a pivotal role in protein interactions among the components of a network. However, it remains unknown how these motifs have contributed to the evolution of the protein network. Here we addressed this issue by a synthetic biology approach. Through the motif programming method, we ha...

The study of biological networks and network motifs can yield significant new insights into systems biology. Previous methods of discovering network motifs – network-centric subgraph enumeration and sampling – have been limited to motifs of 6 to 8 nodes, revealing only the smallest network components. New methods are necessary to identify larger network sub-structures and functional motifs. Her...

Signal search analysis is a general method to discover and characterize sequence motifs that are positionally correlated with a functional site (e.g. a transcription or translation start site). The method has played an instrumental role in the analysis of eukaryotic promoter elements. The signal search analysis server provides access to four different computer programs as well as to a large num...